Overwatch League Stats Lab

Context

Overwatch is a 6v6 FPS (first-person shooter) team game with great variety between heroes who can be played as. Overwatch League (OWL) is the professional esports league of Overwatch. When watching the OWL matches this year, I noticed the power-rankings and predictive statistics by IBM Watson extremely intriguing, so I determined to introduce the datasets into Kaggle. I, myself, really want to replicate the predictions and rankings, then testing with the stats lab.

Content

The datasets include players, head-to-head match-ups, and maps. The player historical statistics should contain OWL games from 2018 till now. It's centered around each player, and player's picked hero, its team name, performance, match IDs, etc.

Acknowledgements

Overwatch League Stats Lab has updated and downloadable csv files. And here are some interesting and inspiring questions to look at: https://overwatchleague.com/en-us/news/23303225.

Inspiration

Other than the power rankings and outcome predictions, I plan to look at teamfight stats, first elimination, and first death to compare the team's power.

For Players:

1. Match Report dashboard
2. Rate Ranks dashboard: Who led the league in solo kills/10 mins in 2018 as Junkrat? (min. 60 mins played)
3. Career Totals dashboard
4. Single Records dashboard

For Heroes:

1. Which 4 heroes did one play for 10% or more of his time on assault map attack rounds in the season?
2. Which hero increased in usage from 8% at the end of Stage 4 of 2018 to over 45% in the inaugural season playoffs?

For Matches:

1. Which team played the most matches that ended in a 3-2 score during the 2021 regular season?
2. Which team is entering the 2021 season on a 7-map loss streak?
3. Which team has the fastest completion time on Rialto?